Alternatives and similar repositories for gaussian_mixture_vae

Users that are interested in gaussian_mixture_vae are comparing it to the libraries listed below

• F-Bekerman / Graph-VAE
  ☆44Updated 7 years ago
• sedelmeyer / wasserstein-auto-encoder
  A brief tutorial on the Wasserstein auto-encoder
  ☆83Updated 6 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 2 years ago
• HongtengXu / s-gwl
  Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
  ☆44Updated 5 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 4 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• shionhonda / gae-dgl
  Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
  ☆64Updated 2 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆101Updated 2 years ago
• tufts-ml / graph-generation-vi
  This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph…
  ☆29Updated last month
• leichen2018 / Ring-GNN
  ☆12Updated 5 years ago
• rusty1s / himp-gnn
  Hierarchical Inter-Message Passing for Learning on Molecular Graphs
  ☆79Updated 3 years ago
• guillaumejaume / edGNN
  Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"
  ☆43Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆104Updated 5 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆52Updated 5 years ago
• mori97 / VaDE
  A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)
  ☆39Updated 4 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• mims-harvard / ohmnet
  OhmNet: Representation learning in multi-layer graphs
  ☆83Updated 4 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆135Updated 6 years ago
• lorenzopalloni / wl-graph-kernels
  A Python implementation of a fast approximation of the Weisfeiler-Lehman Graph Kernels.
  ☆24Updated 6 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆125Updated 11 months ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 5 years ago
• alexlyzhov / latent-subspaces
  Implementation of "Learning latent subspaces in variational autoencoders"
  ☆20Updated 5 years ago
• cvignac / SMP
  ☆28Updated 3 years ago
• snap-stanford / miner-data
  ☆64Updated 5 years ago
• benatorc / OTGNN
  OTGNN code
  ☆55Updated 5 years ago
• slim1017 / VaDE
  Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering
  ☆304Updated 7 years ago
• anonymous1025 / Deep-Graph-Translation-
  ☆16Updated 5 years ago